| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font
First page > Show document

Show document Help

Title:Uporaba umetne inteligence v zunanjem revidiranju
Authors:ID Panič, Laura (Author)
ID Kolar, Iztok (Mentor) More about this mentor... New window
Files:.pdf MAG_Panic_Laura_2024.pdf (3,81 MB)
MD5: AAF51A9C1C63E6E77B33D06EDC3D4A6E
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:EPF - Faculty of Business and Economics
Abstract:V zadnjih nekaj letih ima velik vpliv na zunanje revidiranje umetna inteligenca, ki strmi k temu, da lahko revizorjem olajša določena ponavljajoča se dela in jim omogoča, da se ti lahko posvetijo nalogam, ki prinašajo dodano vrednost zunanji reviziji. V tem magistrskem delu je predstavljena uporaba umetne inteligence v zunanjem revidiranju skozi do sedaj objavljeno literaturo, opravljena pa je tudi raziskava o dejanskem poznavanju in uporabi umetne inteligence v zunanji reviziji računovodskih izkazov v Sloveniji. Naloga podrobneje obravnava tehnologije umetne inteligence, analitiko masovnih podatkov, globoko učenje, veriženje blokov in robotsko avtomatizacijo procesov. V teoretičnem delu smo opredelili zunanjo revizijo in umetno inteligenco ter kronološko predstavili njun razvoj. Predstavljene so tehnologije umetne inteligence, njihova dosedanja uporaba ter morebitne prednosti in pomanjkljivosti vključitve posamezne tehnologije umetne inteligence v revizijski proces. Ugotavljamo, da bi vključitev tehnologij umetne inteligence pripomogla predvsem k večji učinkovitosti in h kakovosti zunanje revizije, k zmanjšanju in avtomatizaciji ponavljajočih se revizijskih nalog, hitrejšemu pregledu in obdelavi podatkov, možnostim testiranja celotne populacije in nenazadnje bi lahko omogočila neprekinjeno revizijo. Uporaba umetne inteligence v reviziji bo za revizorja pomenila pridobitev novega znanja in spretnosti ter dodatna izobraževanja. Na drugi strani pa vključitev tehnologij umetne inteligence prinaša skrb za višje stroške revizije, zaupnosti informacij in varnosti pred kibernetskimi napadi ter pomanjkanje pripravljenosti infrastrukture. V praktičnem delu magistrskega dela je prikazan postopek zbiranja podatkov, pridobljenih s pomočjo anketnega vprašalnika. Z opisno statistično analizo predstavimo pridobljene rezultate vprašanj, ki so bila obdelana s programskim orodjem IBM SPSS. Za ugotavljanje razlik med spremenljivkama spol in zaposlenost anketirancev uporabimo t-test ter za spremenljivko starost anketirancev statistični test ANOVA. Uporabljeni testi pokažejo, da ni statistično značilnih razlik med demografskimi spremenljivkami: spol, starost in zaposlenost anketirancev. Na podlagi povprečnih vrednostih spremenljivk ugotavljamo določene razlike med demografskimi spremenljivkami, ki so v nalogi grafično prikazane. Na podlagi analize podatkov ugotavljamo, da anketirani revizorji v Sloveniji pri svojem delu že uporabljajo umetno inteligenco, ampak velika večina ne uporablja tehnologij, ki so podrobneje predstavljene v tem magistrskem delu. Tehnologija, ki jo revizorji največ uporabljajo, je analitika masovnih podatkov. Revizorji, anketirani v raziskavi, ki so zaposleni v revizijskih družbah Big 4, uporabljajo tehnologije umetne inteligence v povprečju nekoliko več kot revizorji, ki so zaposleni v drugih revizijskih družbah v Sloveniji. Ugotavljamo tudi, da anketirani revizorji nimajo visokega strokovnega znanja o tehnologijah umetne inteligence. Analitika masovnih podatkov je tehnologija, o kateri imajo revizorji največ strokovnega znanja v primerjavi z ostalimi tehnologijami. Rezultati raziskave pokažejo, da so revizorji pričeli z uporabo umetne inteligence zaradi prihranka časa, večje učinkovitosti in hitrejše analize podatkov. Ugotavljamo, da lahko revizorji s pomočjo rešitev umetne inteligence obdelajo več podatkov, kot jih lahko obdelajo brez uporabe umetne inteligence. Uporaba umetne inteligence omogoča revizorjem, da se čas revidiranja skrajša, čeprav je kar nekaj anketiranih mnenja, da čas revidiranja ostaja enak. Anketirani revizorji so mnenja, da bo umetna inteligenca v prihodnosti spremenila poklic zunanjega revizorja. Predvsem se bodo zmanjšala rutinska dela, proces pa bo v veliki meri avtomatiziran in dela bodo opravljena veliko hitreje.
Keywords:zunanja revizija, umetna inteligenca, analitika masovnih podatkov, globoko učenje, veriženje blokov, robotska avtomatizacija procesov
Place of publishing:Maribor
Publisher:L. Panič, I. Bedrač
Year of publishing:2024
PID:20.500.12556/DKUM-89159 New window
UDC:657.6:004.8
COBISS.SI-ID:206847747 New window
Publication date in DKUM:24.09.2024
Views:0
Downloads:35
Metadata:XML DC-XML DC-RDF
Categories:EPF
:
PANIČ, Laura, 2024, Uporaba umetne inteligence v zunanjem revidiranju [online]. Master’s thesis. Maribor : L. Panič, I. Bedrač. [Accessed 13 April 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=89159
Copy citation
  
Average score:
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
(0 votes)
Your score:Voting is allowed only for logged in users.
Share:Bookmark and Share


Searching for similar works...Please wait....
Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.

Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:20.06.2024

Secondary language

Language:English
Title:The use of artificial intelligence in external auditing
Abstract:In recent years, artificial intelligence has had a major impact on external auditing, which aims to make certain repetitive tasks easier for auditors and allow them to focus on tasks that bring added value to external auditing.This master's thesis discusses the use of artificial intelligence in external auditing as portrayed in the literature before presenting research on the actual knowledge and use of artificial intelligence in the external auditing of financial statements in Slovenia. The thesis also covers artificial intelligence technologies, big data analytics, deep learning, blockchains, and robotic process automation. In the theoretical section, we define external auditing and artificial intelligence and present their development chronologically. We then discuss artificial intelligence technologies, their current use, and the potential advantages and disadvantages of including individual artificial intelligence technologies in the audit process. We conclude that the inclusion of artificial intelligence technologies would contribute to greater efficiency and quality in external audits, the reduction and automation of repetitive tasks, faster review and processing of data, the possibility of testing the entire population, and, last but not least, it could enable continuous auditing. For the auditor, the use of artificial intelligence in auditing will mean the acquisition of new knowledge and skills, as well as additional training. The inclusion of artificial intelligence technologies also causes concern about higher costs, information confidentiality and protection against cyber attacks, and a lack of infrastructure. In the practical section, we present the process of collecting data obtained through a survey. We present the results through a descriptive statistical analysis of the questions, which were processed with IBM SPSS software. We used a t-test to determine the differences between the gender and employment variables, and the ANOVA statistical test for the age variable. The tests showed that there were no statistically significant differences between the demographic variables of gender, age, and employment. Based on the average values of the variables, we determined certain differences between the demographic variables, which we demonstrate graphically. Based on the data analysis, we found that the surveyed auditors in Slovenia already used artificial intelligence in their work, but the vast majority did not use the technologies presented in this master's thesis. The technology most used by auditors is big data analytics. On average, the auditors who were employed by the Big 4 audit firms used artificial intelligence technologies slightly more than auditors who were employed by other audit firms in Slovenia. We also note that the surveyed auditors did not have a high level of expertise in artificial intelligence technologies. The surveyed auditors had the most expertise in big data analytics. The results of the survey showed that auditors started using artificial intelligence to save time, for greater efficiency, and for faster data analysis. We found that auditors can process more data with the help of artificial intelligence solutions than they can without the use of artificial intelligence. The use of artificial intelligence allows auditors to reduce audit time, although quite a few respondents stated that audit time remains the same. The surveyed auditors were of the opinion that artificial intelligence will change the profession of external auditor in the future. Above all, routine work will be reduced, the process will be largely automated, and work will be done much faster.
Keywords:external audit, artificial intelligence, big data analytics, deep learning, blockchains, robotic process automation


Comments

Leave comment

You must log in to leave a comment.

Comments (0)
0 - 0 / 0
 
There are no comments!


Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica